From 8b0cf4e574390738ee33f7ff334dd5f5109b7819 Mon Sep 17 00:00:00 2001
From: TheSiahxyz <164138827+TheSiahxyz@users.noreply.github.com>
Date: Wed, 1 Apr 2026 18:37:11 +0900
Subject: feat(strategy): add technical indicators library (ATR, ADX, RSI,
 MACD, Bollinger, Stochastic, OBV)

---
 .../strategies/indicators/momentum.py              | 36 ++++++++++++++++++++++
 1 file changed, 36 insertions(+)
 create mode 100644 services/strategy-engine/strategies/indicators/momentum.py

(limited to 'services/strategy-engine/strategies/indicators/momentum.py')

diff --git a/services/strategy-engine/strategies/indicators/momentum.py b/services/strategy-engine/strategies/indicators/momentum.py
new file mode 100644
index 0000000..395c52d
--- /dev/null
+++ b/services/strategy-engine/strategies/indicators/momentum.py
@@ -0,0 +1,36 @@
+"""Momentum indicators: RSI, Stochastic."""
+import pandas as pd
+import numpy as np
+
+
+def rsi(closes: pd.Series, period: int = 14) -> pd.Series:
+    """RSI using Wilder's smoothing (EMA-based)."""
+    delta = closes.diff()
+    gain = delta.clip(lower=0)
+    loss = -delta.clip(upper=0)
+    avg_gain = gain.ewm(com=period - 1, min_periods=period).mean()
+    avg_loss = loss.ewm(com=period - 1, min_periods=period).mean()
+    rs = avg_gain / avg_loss
+    rsi_vals = pd.Series(np.where(avg_loss == 0, 100.0, 100 - (100 / (1 + rs))), index=closes.index)
+    # Keep NaN where we don't have enough data
+    rsi_vals[:period] = np.nan
+    return rsi_vals
+
+
+def stochastic(
+    highs: pd.Series,
+    lows: pd.Series,
+    closes: pd.Series,
+    k_period: int = 14,
+    d_period: int = 3,
+) -> tuple[pd.Series, pd.Series]:
+    """Stochastic Oscillator.
+
+    Returns: (%K, %D)
+    """
+    lowest_low = lows.rolling(window=k_period).min()
+    highest_high = highs.rolling(window=k_period).max()
+    denom = highest_high - lowest_low
+    k = 100 * (closes - lowest_low) / denom.replace(0, float("nan"))
+    d = k.rolling(window=d_period).mean()
+    return k, d
-- 
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